diff --git a/package/lib/background.py b/package/lib/background.py index 17bb8a8..2f88753 100755 --- a/package/lib/background.py +++ b/package/lib/background.py @@ -63,15 +63,15 @@ def display_bkg(data, background, std_bkg, headers, histograms=None, binning=Non ax.set_xlabel("Observation date and time") ax.set_ylabel(r"Flux [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]") plt.legend() - if not (savename is None): + if savename is not None: this_savename = deepcopy(savename) - if not savename[-4:] in [".png", ".jpg", ".pdf"]: + if savename[-4:] not in [".png", ".jpg", ".pdf"]: this_savename += "_background_flux.pdf" else: this_savename = savename[:-4] + "_background_flux" + savename[-4:] fig.savefig(path_join(plots_folder, this_savename), bbox_inches="tight") - if not (histograms is None): + if histograms is not None: filt_obs = {"POL0": 0, "POL60": 0, "POL120": 0} fig_h, ax_h = plt.subplots(figsize=(10, 6), constrained_layout=True) for i, (hist, bins) in enumerate(zip(histograms, binning)): @@ -85,7 +85,7 @@ def display_bkg(data, background, std_bkg, headers, histograms=None, binning=Non label=headers[i]["filtnam1"] + " (Obs " + str(filt_obs[headers[i]["filtnam1"]]) + ")", ) ax_h.plot([background[i] * convert_flux[i], background[i] * convert_flux[i]], [hist.min(), hist.max()], "x--", color="C{0:d}".format(i), alpha=0.8) - if not (coeff is None): + if coeff is not None: # ax_h.plot(bins*convert_flux[i], gausspol(bins, *coeff[i]), '--', color="C{0:d}".format(i), alpha=0.8) ax_h.plot(bins * convert_flux[i], gauss(bins, *coeff[i]), "--", color="C{0:d}".format(i), alpha=0.8) ax_h.set_xscale("log") @@ -95,9 +95,9 @@ def display_bkg(data, background, std_bkg, headers, histograms=None, binning=Non ax_h.set_ylabel(r"Number of pixels in bin") ax_h.set_title("Histogram for each observation") plt.legend() - if not (savename is None): + if savename is not None: this_savename = deepcopy(savename) - if not savename[-4:] in [".png", ".jpg", ".pdf"]: + if savename[-4:] not in [".png", ".jpg", ".pdf"]: this_savename += "_histograms.pdf" else: this_savename = savename[:-4] + "_histograms" + savename[-4:] @@ -113,7 +113,7 @@ def display_bkg(data, background, std_bkg, headers, histograms=None, binning=Non # plots im2 = ax2.imshow(data0, norm=LogNorm(data0[data0 > 0.0].mean() / 10.0, data0.max()), origin="lower", cmap="gray") ax2.imshow(bkg_data0, origin="lower", cmap="Reds", alpha=0.5) - if not (rectangle is None): + if rectangle is not None: x, y, width, height, angle, color = rectangle[0] ax2.add_patch(Rectangle((x, y), width, height, edgecolor=color, fill=False, lw=2)) ax2.annotate( @@ -128,14 +128,14 @@ def display_bkg(data, background, std_bkg, headers, histograms=None, binning=Non fig2.subplots_adjust(hspace=0, wspace=0, right=1.0) fig2.colorbar(im2, ax=ax2, location="right", aspect=50, pad=0.025, label=r"Flux [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]") - if not (savename is None): + if savename is not None: this_savename = deepcopy(savename) - if not savename[-4:] in [".png", ".jpg", ".pdf"]: + if savename[-4:] not in [".png", ".jpg", ".pdf"]: this_savename += "_" + filt + "_background_location.pdf" else: this_savename = savename[:-4] + "_" + filt + "_background_location" + savename[-4:] fig2.savefig(path_join(plots_folder, this_savename), bbox_inches="tight") - if not (rectangle is None): + if rectangle is not None: plot_obs( data, headers, @@ -145,7 +145,7 @@ def display_bkg(data, background, std_bkg, headers, histograms=None, binning=Non savename=savename + "_background_location", plots_folder=plots_folder, ) - elif not (rectangle is None): + elif rectangle is not None: plot_obs(data, headers, vmin=data[data > 0.0].min(), vmax=data[data > 0.0].max(), rectangle=rectangle) plt.show() @@ -325,7 +325,7 @@ def bkg_hist(data, error, mask, headers, sub_type=None, subtract_error=True, dis for i, image in enumerate(data): # Compute the Count-rate histogram for the image n_mask = np.logical_and(mask, image > 0.0) - if not (sub_type is None): + if sub_type is not None: if isinstance(sub_type, int): n_bins = sub_type elif sub_type.lower() in ["sqrt"]: diff --git a/package/lib/reduction.py b/package/lib/reduction.py index 24d406f..247abc3 100755 --- a/package/lib/reduction.py +++ b/package/lib/reduction.py @@ -1079,7 +1079,7 @@ def polarizer_avg(data_array, error_array, data_mask, headers, FWHM=None, scale= err120 = np.sqrt(np.sum(err120_array**2, axis=0)) / pol120_t polerr_array = np.array([err0, err60, err120]) - if not (FWHM is None) and (smoothing.lower() in ["gaussian", "gauss", "weighted_gaussian", "weight_gauss"]): + if (FWHM is not None) and (smoothing.lower() in ["gaussian", "gauss", "weighted_gaussian", "weight_gauss"]): # Smooth by convoluting with a gaussian each polX image. pol_array, polerr_array = smooth_data(pol_array, polerr_array, data_mask, pol_headers, FWHM=FWHM, scale=scale, smoothing=smoothing) pol0, pol60, pol120 = pol_array @@ -1251,7 +1251,7 @@ def compute_Stokes(data_array, error_array, data_mask, headers, FWHM=None, scale I_stokes[i, j], Q_stokes[i, j], U_stokes[i, j] = np.dot(coeff_stokes, pol_flux[:, i, j]).T Stokes_cov[:, :, i, j] = np.dot(coeff_stokes, np.dot(pol_cov[:, :, i, j], coeff_stokes.T)) - if not (FWHM is None) and (smoothing.lower() in ["weighted_gaussian_after", "weight_gauss_after", "gaussian_after", "gauss_after"]): + if (FWHM is not None) and (smoothing.lower() in ["weighted_gaussian_after", "weight_gauss_after", "gaussian_after", "gauss_after"]): smoothing = smoothing.lower()[:-6] Stokes_array = np.array([I_stokes, Q_stokes, U_stokes]) Stokes_error = np.array([np.sqrt(Stokes_cov[i, i]) for i in range(3)]) diff --git a/package/lib/utils.py b/package/lib/utils.py index 04ec9f9..3918292 100755 --- a/package/lib/utils.py +++ b/package/lib/utils.py @@ -41,7 +41,7 @@ def sci_not(v, err, rnd=1, out=str): else: output[0] += r" $\pm$ {0}".format(round(err * 10**power, rnd)) output.append(round(err * 10**power, rnd)) - if out == str: + if out is str: return output[0] + r")e{0}".format(-power) else: return *output[1:], -power